This first of three reports on a computational study of a drop-laden temporal mixing layer presents the results of direct numerical simulations (DNS) of well-resolved flow fields and the derivation of the large-eddy simulation (LES) equations that would govern the larger scales of a turbulent flow field. The mixing layer consisted of two counterflowing gas streams, one of which was initially laden with evaporating liquid drops. The gas phase was composed of two perfect gas species, the carrier gas and the vapor emanating from the drops, and was computed in an Eulerian reference frame, whereas each drop was tracked individually in a Lagrangian manner. The flow perturbations that were initially imposed on the layer caused mixing and eventual transition to turbulence. The DNS database obtained included transitional states for layers with various liquid mass loadings. For the DNS, the gas-phase equations were the compressible Navier-Stokes equations for conservation of momentum and additional conservation equations for total energy and species mass. These equations included source terms representing the effect of the drops on the mass, momentum, and energy of the gas phase. From the DNS equations, the expression for the irreversible entropy production (dissipation) was derived and used to determine the dissipation due to the source terms. The LES equations were derived by spatially filtering the DNS set and the magnitudes of the terms were computed at transitional states, leading to a hierarchy of terms to guide simplification of the LES equations. It was concluded that effort should be devoted to the accurate modeling of both the subgridscale fluxes and the filtered source terms, which were the dominant unclosed terms appearing in the LES equations.
This work was done by Nora A. Okong'o and Josette Bellan of Caltech for NASA’s Jet Propulsion Laboratory. For further information, access the Technical Support Package (TSP) free on-line at www.techbriefs.com/tsp under the Physical Sciences category. NPO-30719
This Brief includes a Technical Support Package (TSP).
Part 1 of a Computational Study of a Drop-Laden Mixing layer
(reference NPO-30719) is currently available for download from the TSP library.
Don't have an account?
Overview
The document is a Technical Support Package for Part 1 of a computational study focused on a drop-laden mixing layer, prepared under the sponsorship of NASA. It is part of the NASA Tech Briefs and aims to disseminate findings from aerospace-related developments that have potential technological, scientific, or commercial applications.
The study, conducted by researchers Nora A. Okong'o and Josette Bellan, employs Direct Numerical Simulation (DNS) to investigate the complex dynamics of a three-dimensional mixing layer that contains liquid drops. This research is significant as it enhances the understanding of fluid mechanics, particularly in scenarios where droplets interact with turbulent flows. The mixing layer is a critical area of study in various applications, including combustion processes, spray dynamics, and atmospheric phenomena.
The document outlines the methodology used in the simulations, emphasizing the importance of accurately modeling the interactions between the liquid drops and the surrounding fluid. The findings from this research could lead to improved predictions of mixing and evaporation processes, which are essential in fields such as aerospace engineering, environmental science, and industrial applications.
Additionally, the Technical Support Package provides information on how to access further resources and assistance from NASA's Scientific and Technical Information (STI) Program Office. It includes contact details for the NASA STI Help Desk, which can provide additional support and information related to the research.
Overall, this document serves as a foundational resource for understanding the behavior of drop-laden mixing layers and highlights the potential implications of this research in advancing technology and scientific knowledge. The insights gained from this study are expected to contribute to the development of more efficient systems in various industries, showcasing the broader relevance of the research conducted under NASA's auspices.
